Taking pluralism seriously:Embedded moralities in management accounting and control systems

Professor Norman Macintosh has long been a leading, and at times a dissonant, voice in critical accounting studies, exhibiting an intellectual dexterity seldom encountered in the accounting academy. His work ranges from the application of traditional organizational theories within work organizations to poststructural renderings of capital market exigencies. Here, we consider and extend Professor Macintosh's work contemplating the morality embedded within, and propagated by, management accounting and control systems (macs). We begin with Macintosh (1995) employing structuration theory in investigating the ethics of profit manipulation within large, decentralized corporations. The work highlights the fundamental dialectical contradictions within these work organizations, demonstrates the indeterminacy of traditional ethical reasoning, and shows the extent to which macs provide legitimating underpinnings for management action. We propose to extend the conversation using the tools provided in Macintosh's subsequent work: a Levinasian ethic (Macintosh et al., 2009), and heteroglossic accounting (Macintosh, 2002)—both emerging from his poststructuralist predilections. A Levinasian perspective provides an ontologically grounded ethic, and heteroglossic accounting calls for multiple accountings representing alternative moral voices. A critical dialogic framework is proposed as a theoretic for imagining heteroglossic accounting that takes pluralism seriously by recognizing the reality of irresolvable differences and asymmetric power relationships associated with assorted moral perspectives.

Substrate specificity of bacterial oligosaccharyltransferase suggests a common transfer mechanism for the bacterial and eukaryotic systems

The PglB oligosaccharyltransferase (OTase) of Campylobacter jejuni can be functionally expressed in Escherichia coli, and its relaxed oligosaccharide substrate specificity allows the transfer of different glycans from the lipid carrier undecaprenyl pyrophosphate to an acceptor protein. To investigate the substrate specificity of PglB, we tested the transfer of a set of lipid-linked polysaccharides in E. coli and Salmonella enterica serovar Typhimurium. A hexose linked to the C-6 of the monosaccharide at the reducing end did not inhibit the transfer of the O antigen to the acceptor protein. However, PglB required an acetamido group at the C-2. A model for the mechanism of PglB involving this functional group was proposed. Previous experiments have shown that eukaryotic OTases have the same requirement, suggesting that eukaryotic and prokaryotic OTases catalyze the transfer of oligosaccharides by a conserved mechanism. Moreover, we demonstrated the functional transfer of the C. jejuni glycosylation system into S. enterica. The elucidation of the mechanism of action and the substrate specificity of PglB represents the foundation for engineering glycoproteins that will have an impact on biotechnology.

Nonlinear electrostatic excitations of charged dust in degenerate ultra-dense quantum dusty plasmas

The linear and nonlinear properties of low-frequency electrostatic excitations of charged dust particles (or defects) in a dense collisionless, unmagnetized Thomas-Fermi plasma are investigated. A fully ionized three-component model plasma consisting of electrons, ions, and negatively charged massive dust grains is considered. Electrons and ions are assumed to be in a degenerate quantum state, obeying the Thomas-Fermi density distribution, whereas the inertial dust component is described by a set of classical fluid equations. Considering large-amplitude stationary profile travelling-waves in a moving reference frame, the fluid evolution equations are reduced to a pseudo-energy-balance equation, involving a Sagdeev-type potential function. The analysis describes the dynamics of supersonic dust-acoustic solitary waves in Thomas-Fermi plasmas, and provides exact predictions for their dynamical characteristics, whose dependence on relevant parameters (namely, the ion-to-electron Fermi temperature ratio, and the dust concentration) is investigated. An alternative route is also adopted, by assuming weakly varying small-amplitude disturbances off equilibrium, and then adopting a multiscale perturbation technique to derive a Korteweg–de Vries equation for the electrostatic potential, and finally solving in terms for electric potential pulses (electrostatic solitons). A critical comparison between the two methods reveals that they agree exactly in the small-amplitude, weakly superacoustic limit. The dust concentration (Havnes) parameter h = Zd0nd0/ne0 affects the propagation characteristics by modifying the phase speed, as well as the electron/ion Fermi temperatures. Our results aim at elucidating the characteristics of electrostatic excitations in dust-contaminated dense plasmas, e.g., in metallic electronic devices, and also arguably in supernova environments, where charged dust defects may occur in the quantum plasma regime.

Modelling 3D camera movement for vibration characterisation and multiple object identification with application to lighting assessment

Utilising cameras as a means to survey the surrounding environment is becoming increasingly popular in a number of different research areas and applications. Central to using camera sensors as input to a vision system, is the need to be able to manipulate and process the information captured in these images. One such application, is the use of cameras to monitor the quality of airport landing lighting at aerodromes where a camera is placed inside an aircraft and used to record images of the lighting pattern during the landing phase of a flight. The images are processed to determine a performance metric. This requires the development of custom software for the localisation and identification of luminaires within the image data. However, because of the necessity to keep airport operations functioning as efficiently as possible, it is difficult to collect enough image data to develop, test and validate any developed software. In this paper, we present a technique to model a virtual landing lighting pattern. A mathematical model is postulated which represents the glide path of the aircraft including random deviations from the expected path. A morphological method has been developed to localise and track the luminaires under different operating conditions. © 2011 IEEE.

Centres, Peripheries and Party Systems: nested secession processes in Great Britain and Ireland

The seminal work of Lipset and Rokkan, which explores how party systems evolved organically from nineteenth-century roots, has generally been applied in states which have enjoyed a long-standing territorial identity. Their model's emphasis on stability and predictability can, however, be reconciled with circumstances where the very identity of the state itself is an issue. This article explores the capacity of the model to explain party divisions in three nested contexts: the pre-1922 United Kingdom, which encountered problems with its Celtic peripheries, and especially with Ireland; independent Ireland, where a unique party system developed, largely in response to a broader historical and geographical context; and Northern Ireland, where party politics fossilised in the 1880s, and began to unfreeze only in the 1970s. The article argues that the Lipset–Rokkan model casts valuable light on these processes, which in turn contribute to the theoretical richness of the model.

Phase Equilibria of Binary and Ternary Systems Containing ILs, Dodecane, and Cyclohexanecarboxylic Acid

This paper reports both the binary and ternary phase behavior of ionic liquids for extracting cyclohexanecarboxylic acid (CCA) from dodecane. This system is a model for the extraction of acids representative of naphthenic acids found in crude oils. In order to develop an effective ternary liquid-liquid extraction system the preliminary selection of ionic liquids was based on CCA miscibility and the dodecane immiscibility with selected ILs. A wide range of ILs based on different cations, anions, cation alkyl-chain length, as well as the effect of temperature on the overall fluid phase behavior is reported. Factors such as variation of cation group, anion effect, alkyl-chain length, and temperature all impact the extraction to various degrees. The largest effects were found to be the lipophilicity of the IL cation and the co-ordination ability of the anion. While CCA capacity increased with lipophilicity of the cation, as did the dodecane. Highly coordinating anions such as trifluoroacetate and triflate demonstrated that highly efficient extraction could be obtained producing favorable tie-lines in the ternary phase diagram. Overall, this study demonstrates that ILs can selectively extract acids from hydrocarbon streams and offers possible treatment solutions for problems associated with the processing of high acid crude oils.

Dynamic Axle Force and Road Profile Identification Using a Moving Vehicle

In the interaction between vehicles, pavements and bridges, it is essential to aim towards a reduction of vehicle axle forces to promote longer pavement life spans and to prevent bridges loads becoming too high. Moreover, as the road surface roughness affects the vehicle dynamic forces, an efficient monitoring of pavement condition is also necessary to achieve this aim. This paper uses a novel algorithm to identify the dynamic interaction forces and pavement roughness from vehicle accelerations in both theoretical simulations and a laboratory experiment; moving force identification theory is applied to a vehicle model for this purpose. Theoretical simulations are employed to evaluate the ability of the algorithm to predict forces over a range of bridge spans and to evaluate the influence of road roughness level on the accuracy of the results. Finally, in addressing the challenge for the real-world problem, the effects of vehicle configuration and speed on the predicted road roughness are also investigated in a laboratory experiment.

Quantitative Analysis of Fault and Fracture Systems and their Impact on Groundwater Flow in Irish Bedrock Aquifers

Fault and fracture systems are the most important store and pathway for groundwater in Ireland’s bedrock aquifers, either directly as conductive flow structures, or indirectly as the locus for the development of dolomitised limestone and karst. This article presents the preliminary results of a study involving the quantitative analysis of fault and fracture systems in the broad range of Irish bedrock types and a consideration of their impact on groundwater flow. The principal aims of the project are to develop generic conceptual models for different fault/fracture systems in different lithologies and at different depths, and to link them to observed groundwater behaviour. Here we briefly describe the geometrical characteristics of the main post-Devonian fault/fracture systems controlling groundwater flow from field observations at outcrops, quarries and mines. The structures range from Lower Carboniferous normal faults through to Variscan-related faults and veins, with the most recent structures including Tertiary strike-slip faults and ubiquitous uplift-related joint systems. The geometrical characteristics of different fault/fracture systems combined with observations of groundwater behaviour in both quarry and mine localities, can be linked to general flow and transport conceptualisations of Irish fractured bedrock. Most importantly they also provide a basis for relating groundwater flow to particular fault/fracture systems and their expression with depth and within different lithological sequences, as well as their regional variability.

On Regression Methods for Virtual Metrology in Semiconductor Manufacturing

Virtual metrology (VM) aims to predict metrology values using sensor data from production equipment and physical metrology values of preceding samples. VM is a promising technology for the semiconductor manufacturing industry as it can reduce the frequency of in-line metrology operations and provide supportive information for other operations such as fault detection, predictive maintenance and run-to-run control. The prediction models for VM can be from a large variety of linear and nonlinear regression methods and the selection of a proper regression method for a specific VM problem is not straightforward, especially when the candidate predictor set is of high dimension, correlated and noisy. Using process data from a benchmark semiconductor manufacturing process, this paper evaluates the performance of four typical regression methods for VM: multiple linear regression (MLR), least absolute shrinkage and selection operator (LASSO), neural networks (NN) and Gaussian process regression (GPR). It is observed that GPR performs the best among the four methods and that, remarkably, the performance of linear regression approaches that of GPR as the subset of selected input variables is increased. The observed competitiveness of high-dimensional linear regression models, which does not hold true in general, is explained in the context of extreme learning machines and functional link neural networks.